LinkedIn Data Scraper and Miro Integration

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Enrich Miro boards with real-time professional data: automatically pull profiles from LinkedIn Data Scraper into Miro to visually map networks and accelerate hiring. Latenode’s visual editor and affordable execution pricing makes it easier than ever to scale your talent research and team collaboration.

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LinkedIn Data Scraper

Miro

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect LinkedIn Data Scraper and Miro

Create a New Scenario to Connect LinkedIn Data Scraper and Miro

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a LinkedIn Data Scraper, triggered by another scenario, or executed manually (for testing purposes). In most cases, LinkedIn Data Scraper or Miro will be your first step. To do this, click "Choose an app," find LinkedIn Data Scraper or Miro, and select the appropriate trigger to start the scenario.

Add the LinkedIn Data Scraper Node

Select the LinkedIn Data Scraper node from the app selection panel on the right.

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Configure the LinkedIn Data Scraper

Click on the LinkedIn Data Scraper node to configure it. You can modify the LinkedIn Data Scraper URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Add the Miro Node

Next, click the plus (+) icon on the LinkedIn Data Scraper node, select Miro from the list of available apps, and choose the action you need from the list of nodes within Miro.

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Authenticate Miro

Now, click the Miro node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Miro settings. Authentication allows you to use Miro through Latenode.

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Configure the LinkedIn Data Scraper and Miro Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the LinkedIn Data Scraper and Miro Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring LinkedIn Data Scraper, Miro, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the LinkedIn Data Scraper and Miro integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and Miro (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect LinkedIn Data Scraper and Miro

LinkedIn Data Scraper + Miro + Slack: When a LinkedIn profile is scraped for data, a card is created on a Miro board using that data. A summary of the scraped profile is then posted to a Slack channel.

LinkedIn Data Scraper + Miro + Google Sheets: Automatically collect data from LinkedIn profiles using the LinkedIn Data Scraper. Add the scraped data to a Miro board for visual organization and simultaneously save the data in a Google Sheet for record-keeping and future reference.

LinkedIn Data Scraper and Miro integration alternatives

About LinkedIn Data Scraper

Need LinkedIn data for leads or market insights? Automate scraping profiles and company info inside Latenode workflows. Extract data, enrich it with AI, then push it to your CRM or database. Latenode's visual editor and affordable pricing make data-driven outreach scalable and cost-effective.

About Miro

Automate Miro board updates based on triggers from other apps. Latenode connects Miro to your workflows, enabling automatic creation of cards, text, or frames. Update Miro based on data from CRMs, databases, or project management tools, reducing manual work. Perfect for agile project tracking and visual process management, inside fully automated scenarios.

See how Latenode works

FAQ LinkedIn Data Scraper and Miro

How can I connect my LinkedIn Data Scraper account to Miro using Latenode?

To connect your LinkedIn Data Scraper account to Miro on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select LinkedIn Data Scraper and click on "Connect".
  • Authenticate your LinkedIn Data Scraper and Miro accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I visualize LinkedIn profile data in Miro?

Yes! Latenode lets you automatically push scraped LinkedIn data into Miro boards. Use visual templates to analyze trends and collaborate with your team in real time.

What types of tasks can I perform by integrating LinkedIn Data Scraper with Miro?

Integrating LinkedIn Data Scraper with Miro allows you to perform various tasks, including:

  • Automatically creating Miro sticky notes from scraped LinkedIn profiles.
  • Visualizing candidate profiles on a Miro board for recruitment.
  • Generating mind maps in Miro based on LinkedIn company data.
  • Creating project boards with LinkedIn lead information.
  • Updating Miro diagrams with real-time LinkedIn data insights.

How can I transform scraped LinkedIn data before it goes to Miro?

Latenode allows transforming scraped data using JavaScript or AI before visualizing it on Miro, ensuring data accuracy and relevance.

Are there any limitations to the LinkedIn Data Scraper and Miro integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Rate limits of LinkedIn Data Scraper and Miro APIs apply.
  • Complex data transformations may require JavaScript coding.
  • Miro board design is manual after data population.

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